def benchmarking(self, optd):
if optd['submit_cluster']:
# Pickle dictionary so it can be opened by the job to get the parameters
ample_util.save_amoptd(optd)
script = benchmark_util.cluster_script(optd)
workers_util.run_scripts(
job_scripts=[script],
monitor=monitor,
nproc=optd['nproc'],
job_time=43200,
job_name='benchmark',
submit_cluster=optd['submit_cluster'],
submit_qtype=optd['submit_qtype'],
submit_queue=optd['submit_queue'],
submit_pe_lsf=optd['submit_pe_lsf'],
submit_pe_sge=optd['submit_pe_sge'],
submit_array=optd['submit_array'],
submit_max_array=optd['submit_max_array'],
)
# queue finished so unpickle results
optd.update(ample_util.read_amoptd(optd['results_path']))
else:
benchmark_util.analyse(optd)
ample_util.save_amoptd(optd)
return
def benchmarking(self, optd):
if optd['submit_qtype'] != 'local':
# Pickle dictionary so it can be opened by the job to get the parameters
ample_util.save_amoptd(optd)
script = benchmark_util.cluster_script(optd)
with TaskFactory(
optd['submit_qtype'],
script,
cwd=optd['work_dir'],
environment=optd['submit_pe'],
run_time=43200,
name='benchmark',
nprocesses=optd['nproc'],
max_array_size=optd['submit_max_array'],
queue=optd['submit_queue'],
shell="/bin/bash",
) as task:
task.run()
task.wait(interval=5, monitor_f=monitor)
# queue finished so unpickle results
optd.update(ample_util.read_amoptd(optd['results_path']))
else:
benchmark_util.analyse(optd)
ample_util.save_amoptd(optd)
return
def test_benchmark(self):
pklfile="/home/jmht/ample-dev1/examples/toxd-example/ROSETTA_MR_0/resultsd.pkl"
with open(pklfile) as f: d=pickle.load(f)
bd="/home/jmht/ample-dev1/python/foo"
if not os.path.isdir(bd): os.mkdir(bd)
d['benchmark_dir']=bd
benchmark_util.analyse(d)
def benchmarking(self, optd):
if optd['submit_cluster']:
# Pickle dictionary so it can be opened by the job to get the parameters
ample_util.save_amoptd(optd)
script = benchmark_util.cluster_script(optd)
workers_util.run_scripts(
job_scripts=[script],
monitor=monitor,
nproc=optd['nproc'],
job_time=43200,
job_name='benchmark',
submit_cluster=optd['submit_cluster'],
submit_qtype=optd['submit_qtype'],
submit_queue=optd['submit_queue'],
submit_pe_lsf=optd['submit_pe_lsf'],
submit_pe_sge=optd['submit_pe_sge'],
submit_array=optd['submit_array'],
submit_max_array=optd['submit_max_array'])
# queue finished so unpickle results
optd.update(ample_util.read_amoptd(optd['results_path']))
else:
benchmark_util.analyse(optd)
ample_util.save_amoptd(optd)
return